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Analysis of institutional authors

Navas-Loro, MariaCorresponding AuthorRodriguez-Doncel, VictorAuthorSantana-Perez, IdafenAuthorSanchez, AlbertoAuthor

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November 6, 2024
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Proceedings Paper
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Spanish Corpus for Sentiment Analysis Towards Brands

Publicated to: Syntactic ASP Forgetting with Forks. 10458 680-689 - 2017-01-01 10458(), DOI: 10.1007/978-3-319-66429-3_68

Authors:

Navas-Loro, M; Rodríguez-Doncel, V; Santana-Perez, I; Sánchez, A
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Affiliations

Havas Media, Madrid, Spain - Author
Univ Politecn Madrid, Ontol Engn Grp, Madrid, Spain - Author

Abstract

Posts published in the social media are a good source of feedback to assess the impact of advertising campaigns. Whereas most of the published corpora of messages in the Sentiment Analysis domain tag posts with polarity labels, this paper presents a corpus in Spanish language where tagging has been made using 8 predefined emotions: love-hate, happiness-sadness, trust-fear, satisfaction-dissatisfaction. In every post, extracted from Twitter, sentiments have been annotated towards each specific brand under study. The corpus is published as a collection of RDF resources with links to external entities. Also a vocabulary describing this emotion classification along with other relevant aspects of customer's opinion is provided.
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Keywords

CoefficienCorpusEmotionsNlpOntologyOpinion mininOpinion miningSentiment analysis

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-25:

  • WoS: 6
  • Scopus: 7
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-25:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 22.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 22 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 18.

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/93615/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 23
  • Downloads: 2
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Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (NAVAS LORO, MARIA) and Last Author (SÁNCHEZ SÁNCHEZ, ALBERTO).

the author responsible for correspondence tasks has been NAVAS LORO, MARIA.

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Project objectives

Los objetivos perseguidos en esta aportación son analizar publicaciones en redes sociales para evaluar el impacto de campañas publicitarias, desarrollar un corpus en lengua española etiquetado con ocho emociones predefinidas (amor-odio, felicidad-tristeza, confianza-miedo, satisfacción-insatisfacción), anotar los sentimientos expresados hacia marcas específicas en mensajes extraídos de Twitter, publicar el corpus como una colección de recursos RDF vinculados a entidades externas, y proporcionar un vocabulario que describa esta clasificación emocional junto con otros aspectos relevantes de la opinión del consumidor.
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Most relevant results

El estudio presenta un corpus en español para análisis de sentimiento dirigido a marcas, basado en publicaciones de Twitter. Los resultados más relevantes incluyen: la clasificación de sentimientos en ocho emociones predefinidas (amor-odio, felicidad-tristeza, confianza-miedo, satisfacción-insatisfacción); la anotación de sentimientos específicos hacia cada marca analizada; la publicación del corpus como recursos RDF vinculados a entidades externas; y la provisión de un vocabulario que describe esta clasificación emocional junto con otros aspectos relevantes de la opinión del consumidor. Estos avances permiten un análisis detallado y estructurado de la percepción del consumidor en redes sociales.
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Awards linked to the item

This work has been partially supported by LPS-BIGGER (IDI20141259, Ministerio de Economia y Competitividad), a research assistant grant by the Consejeria de Educacion, Juventud y Deporte de la Comunidad de Madrid partially founded by the European Social Fund (PEJ16/TIC/AI-1984) and a Juan de la Cierva contract.
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